Machine Learning Engineer Python Jobs in Massachusetts

John Hancock's AI team works across the US Insurance business to optimize our sales and marketing activities, make life insurance easy to buy, and streamline in-force and claims operations! We have close relationships with functional leadership across the business and a strong working relationship with technology partners. As part of a 160+ member community of data scientists, John Hancock, and our parent Manulife, you will have an opportunity to network with experts across the globe.

John Hancock is a unit of Manulife Financial Corporation, a leading international financial services group offering insurance and wealth management solutions in the US, Canada, Europe, and Asia!

We are on a transformational journey. We want to remove complexity from the financial services industry, to make people's lives better and decisions easier. Being part of this transformation is hugely exciting and offers talented, ambitious people an amazing opportunity to build a career.

We are seeking a skilled Machine Learning Engineer with a strong focus on building data pipelines, AI solution development, deployment, and monitoring. The ideal candidate will have experience in data ingestion & curation, developing scalable and robust AI solutions, and deploying AI solutions in production following MLOps best practices on Microsoft Azure and Databricks platforms. A strong background in Computer vision, NLP and LLM models will be advantageous in this role.

Position Responsibilities:

• Building of GenAI and AI solutions, including but not limited to analytical model development and implementation, prompt engineering, general all-purpose programming (e.g., Python), testing, communication of results, front end and back-end integration, and iterative development with business subject matter expertise.
• Designing and solutioning AI/GenAI architectures for business teams, specifically for plugin-based solutions and custom AI/GenAI application builds.
• Partner with data engineers and architects to design and implement scalable database solutions and data models, organizing both structured and unstructured data.
• Develop processes for data cleansing, enrichment, and validation to improve quality and reliability.
• Collaborate with data scientists to develop and deploy machine learning models in cloud following best practices.
• Monitor, solve, and optimize data pipelines for performance and efficiency.
• Partner with IT and technology teams to put together data architecture designs, integration procedures, and data management workflows.
• Partner with data and platform partners to implement the best practices in managing data and platforms, supporting AI development and deployment at scale.
• Develop automation scripts and tools to ease the deployment, scaling, and management of data systems within the cloud environment.
• Continuously monitor and improve the performance of AI solutions through data analysis and testing.
• Strong communication to help business partners better understand the use of data, ML models, and AI solutions.

Required Qualifications:

• Experienced in developing and deploying models using AI and GenAI technologies in cloud.
• Experienced in data modeling, ETL/ELT development, and data warehousing.
• Master/PhD degree in a quantitative field such as Data Science, Engineering, Computer Science or related technical field.
• Preferred Qualifications:
• Hands-on experience in developing models solving NLP tasks, including Document Classification, Entity Extraction, Entity Relation Extraction, etc.
• Hands-on experience in processing documents (PDF/Images) using vision and/or language models, as well as OCR techniques.
• Proven experience with Databricks and Azure cloud services and data solutions including but not limited to Azure SQL Data Warehouse, Azure Cosmos DB, Azure Data Lake Storage, Azure Function and Azure Data Factory.
• Proficiency with big data processing frameworks such as Apache Spark and experience with programming languages like Python, Scala, or SQL.
• Skilled in the machine learning modeling life cycle, including exploratory data analysis, data cleansing, feature engineering, model building, deployment and monitoring.
• Good understanding of vectorization and embedding, prompt engineering, RAG, Multi-agent techniques.
• Experience in developing and deploying models in cloud-based environments, specifically Microsoft Azure, and Databricks, following MLOps and DevOps best practices.
• Experience with Git Version Control, Unit/Integration/End-to-End Testing, CI/CD, release management, etc.
• Excellent problem-solving skills and the capacity to work under tight deadlines in a fast-paced environment.
• Previous work in agile development environments and knowledge of project management tools such as JIRA.

When you join our team:

• We'll empower you to learn and grow the career you want.
• We'll recognize and support you in a flexible environment where well-being and inclusion are more than just words.
• As part of our global team, we'll support you in shaping the future you want to see.

#LI-Hybrid

The role being advertised is an existing vacancy.

About Manulife and John Hancock

Manulife Financial Corporation is a leading international financial services provider, helping people make their decisions easier and lives better. To learn more about us, visit https://www.manulife.com/en/about/our-story.html.

Manulife is an Equal Opportunity Employer

At Manulife/John Hancock, we embrace our diversity. We strive to attract, develop and retain a workforce that is as diverse as the customers we serve and to foster an inclusive work environment that embraces the strength of cultures and individuals. We are committed to fair recruitment, retention, advancement and compensation, and we administer all of our practices and programs without discrimination on the basis of race, ancestry, place of origin, colour, ethnic origin, citizenship, religion or religious beliefs, creed, sex (including pregnancy and pregnancy-related conditions), sexual orientation, genetic characteristics, veteran status, gender identity, gender expression, age, marital status, family status, disability, or any other ground protected by applicable law.

It is our priority to remove barriers to provide equal access to employment. A Human Resources representative will work with applicants who request a reasonable accommodation during the application process. All information shared during the accommodation request process will be stored and used in a manner that is consistent with applicable laws and Manulife/John Hancock policies. To request a reasonable accommodation in the application process, contact hr@manulife.com.

Referenced Salary Location

Salary range is expected to be between

Employees also have the opportunity to participate in incentive programs and earn incentive compensation tied to business and individual performance. The actual salary will vary depending on local market conditions, geography and relevant job-related factors such as knowledge, skills, qualifications, experience, and education/training. If you are applying for this role outside of the primary location, please contact hr@manulife.com for the salary range for your location.

Manulife/John Hancock offers eligible employees a wide array of customizable benefits, including health, dental, mental health, vision, short- and long-term disability, life and AD&D insurance coverage, adoption/surrogacy and wellness benefits, and employee/family assistance plans. We also offer eligible employees various retirement savings plans (including pension/401(k) savings plans and a global share ownership plan with employer matching contributions) and financial education and counseling resources. Our generous paid time off program in the U.S. includes up to 11 paid holidays, 3 personal days, 150 hours of vacation, and 40 hours of sick time (or more where required by law) each year, and we offer the full range of statutory leaves of absence.

We use data and analytics technologies, such as artificial intelligence (AI), and automated processing tools, to analyze and process the information you provide to us or third parties in the application process. For more information, please refer to our personal information collection statement.

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